Category Archives: trading

cryptocurrency, economics, finance, technology, trading

Why Dogecoin bulls must watch THIS hurdle after $0.22 rebound

Leave a comment

**Key Takeaways: Why Did Dogecoin Rebound?**

Dogecoin (DOGE) recently bounced at a crucial support level of $0.22, reclaiming both the 20-day and 50-day Exponential Moving Averages (EMAs) while holding above the 100-day EMA trendline. This technical movement has reignited bullish sentiment among traders.

—

### What DOGE Signals Point Toward $0.30?

The surge in DOGE’s price is backed by strong market indicators. Futures Open Interest (OI) jumped to $4.23 billion, highlighting increased speculative and institutional involvement. Additionally, liquidity pockets above $0.25 suggest that traders have a strong appetite for higher price levels, indicating robust bullish positioning.

—

### Technical Analysis: DOGE’s Recent Price Action

Earlier this week, Dogecoin slipped to the key technical support at $0.22 before bouncing back sharply. This support level aligns with the 100-day EMA, reinforcing its reliability. Bulls defended this zone, resulting in a notable 9% daily gain that preserved the broader upward trend.

Following the rebound, DOGE successfully crossed above the 20-day EMA at $0.24 and the 50-day EMA at $0.23. This shift in technical momentum has boosted confidence in a potential rally toward the next resistance level at $0.30.

—

### DOGE On-Chain Metrics Complement Technical Setups

Beyond price action, on-chain data supports the optimistic outlook for DOGE. According to CoinGlass, the DOGE Futures Open Interest surged significantly to $4.23 billion, indicating that more capital is entering the market. Rising OI often points to increasing volatility and greater trader participation.

Moreover, CoinGlass’s DOGE/USDT Liquidation Heatmap reveals multiple liquidity clusters above the $0.25 mark. These clusters act as strong magnets, suggesting that if momentum continues, these levels could attract further buying pressure.

—

### History Repeats at Trendline Support

This recent rebound mirrors past rallies in early July and earlier this month, where DOGE bounced off the trendline support and surged between 15% to 20% within just a few days. Such historical patterns keep traders eyeing $0.30 as the next significant upside target.

However, it’s important to monitor market sentiment closely. If profit-taking intensifies or Funding Rates spike, the bullish outlook might shift. For the moment, both chart patterns and market positioning remain tilted toward a positive trajectory.

—

Stay tuned for updates as DOGE aims to sustain its momentum and possibly test new highs.
https://ambcrypto.com/why-dogecoin-bulls-must-watch-this-hurdle-after-0-22-rebound

business, education, finance, technology, trading

How Beginners Can Transition From Manual To Automated Trading

Leave a comment

Trading has evolved significantly over the years. What once relied heavily on intuition, chart reading, and gut feeling has now shifted toward systematic, data-driven methods. For beginners, moving from manual trading to automated trading can feel overwhelming. However, with structured learning, practical guidance, and the right resources, this transition is entirely achievable.

In this article, we’ll explore how beginners can transition from manual to automated trading, the role of education in facilitating this shift, and how QuantInsti’s quantitative finance courses—including *Automated Trading for Beginners* and their day trading course—help learners acquire real-world skills.

—

### The Challenges of Manual Trading

Manual trading demands constant attention to the markets. Traders must monitor price movements, analyze charts, track news, and make swift decisions. Beginners often face several common challenges:

– **Time-consuming:** Long hours of screen time are required to monitor markets and respond to events.
– **Emotional Influence:** Fear, greed, and impatience can affect decisions, leading to inconsistent results.
– **Limited Data Handling:** Humans can process only so much information at once, often missing hidden patterns.
– **Backtesting Difficulties:** Testing strategies on historical data manually is slow and prone to errors.

While manual trading is excellent for learning market fundamentals, it is often inefficient and not scalable for long-term growth. This is where automated trading becomes a game-changer.

—

### Why Automated Trading Works

Automated trading uses preset rules and computer programs to execute trades. It offers several advantages, especially for beginners:

– **Consistency:** Trades follow defined rules, eliminating emotional biases.
– **Speed:** Computers react faster than humans, capturing opportunities immediately.
– **Data-Driven Decisions:** Algorithms process technical indicators and historical data for informed trading.
– **Backtesting and Optimization:** Strategies can be tested on past data to refine rules before risking real capital.

Automated trading does not replace human judgment; rather, it enhances it. It allows traders to focus on strategy design, risk management, and market analysis instead of reacting impulsively.

—

### Building a Strong Foundation

The first step in moving to automated trading is structured learning. Beginners need to understand market basics, trading strategies, and programming fundamentals.

Quantitative finance courses provide this foundation with modules designed for both beginners and advanced learners. Courses like *Automated Trading for Beginners* teach Python programming, quantitative techniques, and methods to analyze historical market data.

Students explore various strategies, including day trading, event-driven trading, ARIMA, ARCH, GARCH, volatility modeling, and statistical arbitrage.

—

### Learning by Doing

Theory alone is not enough. Beginners must apply what they learn in real-world scenarios. Starting by coding simple strategies such as momentum trading or scalping helps build practical skills.

Backtesting allows learners to evaluate how a strategy performs historically, adjust parameters, and understand market condition impacts. This hands-on approach builds confidence before live trading, ensuring strategies are well understood and risks are managed.

—

### Transitioning from Manual to Automated Day Trading

Day trading is often where beginners first experience the benefits of automation. A dedicated day trading course shows how to automate strategies previously executed manually. Here’s a step-by-step approach for beginners:

1. **Start Small:** Begin with simple strategies like momentum trading or basic indicators. Understand the rules and execution.
2. **Backtest Strategies:** Use historical data to evaluate performance and identify weaknesses without risking real money.
3. **Paper Trading:** Simulate trades in real-time using virtual capital to bridge the gap between testing and live markets.
4. **Live Trading with Risk Management:** Once confident, start live trading with strict stop-loss rules and proper position sizing.

This structured process saves time, reduces errors, and helps build a systematic, disciplined trading practice.

—

### A Learner’s Journey: From Curiosity to Confidence

Consider Xavier Anthony from Canberra, Australia. With a background in engineering and computer science, Xavier was naturally drawn to data and technology and had a strong fascination with financial markets. He experimented with mock trades and tested various strategies but struggled to turn knowledge into consistent results.

Xavier’s breakthrough came when he joined QuantInsti’s Executive Programme in Algorithmic Trading (EPAT). Through the program, he acquired technical skills, mastered backtesting, learned risk management, and honed strategy evaluation.

Today, Xavier confidently develops trading strategies, understands why trades execute, and knows how they fit into a broader portfolio—demonstrating how structured education and practical experience are crucial in transitioning from manual to automated trading.

—

### Tools and Resources for Beginners

QuantInsti offers a comprehensive ecosystem to support learners moving into automated trading:

– **Interactive Notebooks and Coding Exercises:** Learn by doing in an engaging environment.
– **Capstone Projects with Real Market Data:** Apply strategies in realistic, hands-on scenarios.
– **Community and Faculty Support:** Access expert guidance and peer support.
– **Lifetime Access:** Revisit courses, exercises, and projects anytime to sharpen skills.

These resources allow beginners to build expertise gradually without feeling overwhelmed.

—

### Tips for a Smooth Transition

To make the shift from manual to automated trading easier, keep the following tips in mind:

– **Be Patient:** Automation is not a shortcut to instant profits. Start small and focus on learning.
– **Learn from Mistakes:** Use backtesting and paper trading to experiment safely.
– **Prioritize Risk Management:** Effective position sizing and stop-loss rules are essential.
– **Practice Consistently:** Regular coding, testing, and refining improve skills and confidence.
– **Seek Guidance:** Utilize courses, communities, and mentors to avoid common pitfalls.

—

### Final Thoughts

Transitioning from manual to automated trading may seem challenging, but it is vital for long-term success. Automation brings consistency, efficiency, and the ability to analyze vast amounts of data.

QuantInsti’s quantitative finance courses equip beginners with the knowledge, hands-on experience, and confidence needed to design, backtest, and implement automated strategies effectively.

QuantInsti offers a modular, flexible, “learn by coding” approach, including free starter courses and affordable per-course pricing. For advanced learners, the EPAT program provides live classes, expert faculty, placement support, and career opportunities through hiring partners and alumni success stories.

Together, these programs help beginners become skilled, confident traders ready to succeed in today’s dynamic markets.
https://www.freepressjournal.in/latest-news/how-beginners-can-transition-from-manual-to-automated-trading

cryptocurrency, finance, investing, market analysis, trading

Crypto Bloodbath Shakes Market—But Is The Real Storm Still To Come?

Leave a comment

Crypto Absorbs Largest Liquidation Shock of 2025, Analyst Urges Caution

Crypto markets faced their largest liquidation shock of 2025, witnessing the heaviest single-day wipeouts since summer 2023 for Ethereum (ETH) and Solana (SOL), and the biggest since June for Bitcoin (BTC). This triggered a sharp, sentiment-driven downdraft across major cryptocurrencies and large-cap altcoins.

In a video analysis published today, analyst CryptoInsightUK urged restraint, suggesting that the move resembles a leverage flush rather than a structural break. He pointed to liquidity maps, momentum gauges, and market-cap composites that, in his view, still skew constructive once the dust settles.

“Do not rush and panic this morning,” he said at the outset. “The only rush and panic thing that you should be doing at this time is if you just want to buy spot. Nothing has really changed at all.”

### Market Context and Recent Highs

He framed the sell-off against near-all-time-high closes last week across market-cap aggregates:
– Total2 (ex-BTC) closed at about $1.66–$1.67 trillion,
– Total3 (ex-BTC, ex-ETH) at $1.13 trillion,
– Total crypto market cap just shy of $4 trillion at $3.96 trillion.

The message? Zoom out, assess structure, and watch for a familiar bottoming sequence that typically follows abrupt long liquidations.

### Short-Term Roadmap: Classic Liquidity Sweep and Momentum Divergence

The analyst’s short-term roadmap hinges on a classic liquidity sweep plus momentum divergence. After a vertical wick clears resting bids and triggers stops, he anticipates price to chop, revisit, and marginally undercut the intraday low while the RSI forms a higher low.

“What we’re looking for structurally is a higher low on the RSI, perfect if it’s in the oversold area. When we have a higher low on the RSI and a lower low in price action, the momentum of the selling is waning,” he explained, calling this setup a reliable reversal signal. “The higher the timeframe, the better.”

### Crypto Watch: ETH, XRP, DOGE, ADA

He cited fresh examples across majors:

– **Ethereum (ETH):** A drawdown from about $4,400 to $4,000 sliced through a dense cluster of below-price liquidity that had accumulated for weeks. “This is the first time we’ve seen more liquidity above us than we have below since the prior five-wave advance,” he noted, interpreting this as consistent with an ABC correction that may be maturing.

– **XRP:** It pinpointed its only notable pocket of sub-price liquidity, wicking to $2.66, mapped against $2.8–$2.69. He now sees the main liquidity above at $3.40 for XRP, allowing that a brief wick-fill toward today’s low could complete the divergence pattern he’s monitoring.

– **Bitcoin (BTC):** The dominance spike during the flush aligns with his playbook. He described the dominance RSI as massively overbought, “probably like on the hourly as overbought as I’ve seen it,” noting that prior moves into this zone have coincided with local peaks in BTC relative strength before rotation back into large caps and selective alts. This context, together with his zoomed-out view, underpins his claim that bullish sentiment will be rewarded over time—even if the path includes unnerving resets.

– **Dogecoin (DOGE):** While DOGE reclaimed support around $0.22, he cautioned it can still probe the $0.19–$0.20 zone. He flagged the 4-hour RSI as being as depressed as at prior cyclical lows. He disclosed a 2x DOGE long position around $0.225, with no hard stop due to his conviction in the higher-timeframe trend and acceptance of potential further volatility.

– **Cardano (ADA):** It wicked into a mapped liquidity shelf near $0.77, with main liquidity zones at $1.00 and $1.20 on the daily chart—a configuration he views as asymmetrically favorable once the market stabilizes.

### What to Watch Now

Throughout the analysis, the emphasis is clear: today’s damage was amplified by leverage, not fundamentals. “We’ve had a liquidity flush,” he said, referencing a social post that estimated a billion dollars of leverage was flushed out in 30 minutes.

For him, this is positive. “We want to see this leverage reset.”

He cautioned that near-term direction is hostage to U.S. cash-market flows. “The U.S. might wake up and sell, or buy the dip,” he said, but insisted that the larger structures remain intact:

“Weekly, we’re still sitting at all-time highs. Whether the tops are in or not, I don’t think so. I really, really, really, really, really don’t think so.”

His near-term checklist is straightforward: let volatility run its course, look for the RSI higher-low against a marginal price lower-low, and respect predefined support and target zones.

“Take your emotion away and look for structures that you know are bottoming structures,” he advised.

Trader psychology, he added, is as critical as the levels. “These things happen and it feels like a culmination of sentiment: anger, frustration, and now probably despair. If it’s too much, go for a run.”

He reminded that the market doesn’t care about emotions and will do what it will do anyway.

### The Road Ahead

If the real storm is still to come, it lies in the post-flush move—whether that means a final liquidity sweep completing the divergence or a swift rotation lifting majors into overhead liquidity he has mapped.

Either way, he argues, the decisive phase is ahead, not behind:

“Let’s see how things play out. It’s not a time to panic. If you want to be buying things when we’re oversold like this, it’s a decent time to buy.”

—

At press time, ETH traded at $4,185.

*Featured image created with DALL·E; chart sourced from TradingView.com.*
https://www.newsbtc.com/news/crypto-bloodbath-real-storm-still-to-come/